hypedarhypedar
feedtrendsdiscovershowcasearchive
login
login
login
FeedTrendsDiscoverShowcaseArchiveDashboard
Submit Showcase

Trending now

Fine Tuning + Reasoning76Fine Tuning + Reasoning + Inference64Math + Games56
View all trends →

hypedar

AI trend radar for developers. Catch emerging papers, repos, and discussions before the hype peaks.

AboutGitHubDiscord

By the makers of hypedar

Codepawl

Open-source tools for developers.

Explore our tools →
AboutPrivacyTermsX

© 2026 Codepawl

Built by Codepawl·© 2026

About·Terms·Privacy·Security

GitHub·Discord·X

feedtrendsdiscovershowcasearchive
← trends

Llm + Rl + Training

66.0

Build a lightweight, zero-dependency alternative to Ollama that focuses on standard GGUF file execution for edge devices. Prioritize binary size and cold-start time.

+0
activeimplementation gap
rltrainingllmvalue-gradientmoeroutingruntimesearchraginference

Signals (10)

arXiv7d ago

Weakly Supervised Distillation of Hallucination Signals into Transformer Representations

YHN1d ago

The local LLM ecosystem doesn’t need Ollama

arXiv5h ago

Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy Optimization

arXiv5h ago

Reinforcement Learning via Value Gradient Flow

nvidia blog7d ago

Cut Checkpoint Costs with About 30 Lines of Python and NVIDIA nvCOMP

arXiv5h ago

Response-Aware User Memory Selection for LLM Personalization

arXiv4d ago

Can We Still Hear the Accent? Investigating the Resilience of Native Language Signals in the LLM Era

arXiv5h ago

Awakening Dormant Experts:Counterfactual Routing to Mitigate MoE Hallucinations

OpenAI7d ago

Prompting fundamentals

GitHub5d ago

google-research/bert